Senior Applied Scientist - Retail Data & Measurement

The Trade Desk; Bellevue (WA); On-site; USD 125,000 - 229,000; Full time

Benefits offered by this job

Healthcare benefits

401(k) with company match

Stock purchase plan

Parental leave

Job summary

The Trade Desk is seeking an applied scientist to own and improve retail conversion data from source collection to final reports. You will design, implement, and monitor data pipelines, applying rigorous statistics to scale estimates while accounting for bias and uncertainty.

Collaboration with engineers, data scientists, and product managers is essential. Proficiency in Python, SQL, and PySpark, plus experience on distributed systems (EMR/Databricks), will help you drive robust, data-informed

Qualifications

• Experience building statistical solutions and data pipelines at scale.
• Experience estimating population quantities from partial or biased samples.
• Proficient in Python and SQL.
• Experience working with retail, panel, survey, or conversion data.

Responsibilities

• Own retail conversion datasets end to end and be the expert on data sources.
• Explore and process data from multiple retail sources to build datasets and pipelines.
• Apply statistics to scale and project measurements, imputing missing data with honest bounds.
• Monitor data quality and stability of metrics, distinguishing real shifts from noise.
• Reason about how data feeds conversion lift and attribution and validate robustness.
• Partner with cross-functional stakeholders and communicate learnings to steer product decisions.

Skills

Python

SQL

PySpark

Statistics fundamentals

Data processing at scale

Communication with stakeholders

Education

BS/MS with 4+ years in DS/ML

PhD with 2+ years in DS/ML

Tools

EMR

Databricks

Spark

Job description

The Trade Desk is seeking an applied scientist to own and improve retail conversion data from source collection to final reports. You will design, implement, and monitor data pipelines, applying rigorous statistics to scale estimates while accounting for bias and uncertainty.

Collaboration with engineers, data scientists, and product managers is essential. Proficiency in Python, SQL, and PySpark, plus experience on distributed systems (EMR/Databricks), will help you drive robust, data-informed